Nabil Bouaouli: Efficient sensory processing could depend on excitation/inhibition balance: A view from change detection
Talk by Nabil Bouaouli of Ecole Normale Superieure, Paris. Given to the Redwood Center for Theoretical Neuroscience on March 10, 2009 at UC Berkeley.
Run time About 55 minutesProducer Redwood Center for Theoretical NeuroscienceAudio/Visual sound, color
The brain continuously processes the signals that emerge from the dynamic sensory environment. A well admitted view about the strategy applied by the nervous system is that it analyses the “sensory scene” as an ensemble of basis features which constitute the signal (e.g. colors, orientations, tones). Each feature, then, activates specific sensory neurons which are sensitive to its appearance. On the other hand, theses neurons are known to respond more strongly to transient than to steady stimuli. In this work, we hypothesize that they are suited to efficiently detect changes in the environment (i.e. the appearance of their preferred features) as soon as these changes occur and the question we want to answer is how are sensory stimuli detected and coded and what are the mechanisms involved in this process. To address this issue, we provide a probabilistic framework of change detection that goes from functional level to cellular level. Namely requiring the detection of fast and unpredictable changes in the environment, the model predicts the likely sensory circuits needed to achieve this goal.This (micro) circuit involves parallel feedforward excitatory and “delayed” inhibitory pathways and predicts the short-term temporal dynamics of the synapses involved. Moreover, it shows how the biophysical properties of these synapses could be shaped by the statistics of the environment. In terms of sensor coding, our model exhibits naturally adaptive behavior as a built-in process. In response to changes in the level of stimulus fluctuations, the model adapts its sensitivity in qualitatively the same way as visual pathway cells do it. As a key feature of this model is a “bounded” and delayed inhibition that depends on the temporal statistics of the environment, we propose that feedforward inhibition may play a general role in sensory processing over many timescales and argue that the balance between excitation and inhibition may have direct implications on the efficiency of early sensory processing.
May 7, 2009
I seems that your demo was very succesfull, right well I think, thank you.